Search Results (39)

Electronic coupling within InAs/InP quantum dots (QDs) influences carrier lifetime and thus QD laser performance. In this work, vertical electronic coupling between QDs is theoretically investigated based on a structure of five-layer QD stacks. This analysis illustrates that the resonant tunneling, a consequence of coherent coupling between QDs, should be considered for carrier redistribution. The carrier tunneling time of ground states is estimated by studying two structures of uniform and chirped five-layer QD stacks. The impact of resonant tunneling on optical properties of InAs/InP QD Fabery–Perot (FP) lasers, such as threshold current, light power-current temperature dependence, and relative intensity noise, is investigated through a comparison of uniform and chirped QD lasers. It is found that the carrier resonant tunneling leads to an increase in the threshold current, low characteristic temperature, and high relative intensity noise. By using the chirped QD stacks, the optical properties are improved thanks to less resonant tunneling. Full article

Hate speech on social media reproduces norms of inequality and gender stereotypes, disproportionately affecting women. This study proposes a hybrid approach that integrates emotional tone classification with explicit hostility detection to strengthen preventive moderation. We constructed a corpus from three open data sets (1,236,371 records; 1,003,991 after ETL) and represented the text using TF-IDF and contextual RoBERTa embeddings. We trained individual models (RoBERTa fine-tuned, Random Forest, and XGBoost) and a stacking metamodel (Gradient Boosting) that combines their probabilities. On the test set, the ensemble outperformed the base classifiers, achieving accuracy of 0.93 in hate detection and 0.90 in emotion classification, with an AUC of 0.98 for emotion classification. We implemented a RESTful API and a web client to validate the moderation flow before publication, along with an administration panel for auditing. Performance tests in a prototype deployment (Google Colab exposed through an Ngrok tunnel) provided proof-of-concept validation, revealing concurrency limitations from around 300 users due to infrastructure constraints. In general, the results indicate that incorporating emotional tone analysis improves the model’s ability to identify implicit hostility and offers a practical way to promote safer digital environments. The probabilistic outputs produced by the ensemble model were subsequently analyzed using the Bayesian Calibration and Optimal Design under Asymmetric Risk (BACON-AR) framework, which serves as a mathematical post hoc decision layer for evaluating classification behaviour under unequal error costs. Rather than modifying the trained architecture or improving its predictive performance, the framework identifies a cost-sensitive operating threshold that minimizes the total expected risk under the selected asymmetric cost configuration. The experiments were conducted using an English-language data set; therefore, the findings of this study are limited to hate speech detection in English. Full article

Perpendicular magnetic tunnel junctions (p-MTJs) rely on synthetic antiferromagnets (SAFs) as reference layers to achieve strong perpendicular magnetic anisotropy (PMA) together with stable interlayer exchange coupling. In this study, we present a comparative materials study of buffer and spacer layer engineering in Co/Pt-based perpendicular synthetic antiferromagnets (p-SAFs). The influence of buffer layer selection, number of multilayer repeats, and annealing at 330 °C for 30 min on PMA and interlayer exchange coupling is systematically examined. Co/Pt multilayers with four and six repeats were grown on Ta/Ru and Ta/CuN buffer layers separately, followed by the fabrication of SAF structures incorporating Ru spacers with thickness between 0.60 and 0.80 nm. Magnetic measurements show that Ta/Ru-buffered structures exhibit squarer hysteresis loops, higher remanence, and greater tolerance to annealing at 330 °C for 30 min compared to Ta/CuN-buffered counterparts. The SAF structures display clear two-step magnetization reversal and robust antiferromagnetic coupling across the investigated Ru thickness range, with large exchange fields and bias fields in the deposited state. Although annealing reduces the absolute coupling strength, a Ru spacer thickness of 0.60 nm retains the strongest antiferromagnetic response within the studied thermal budget. These results underscore the importance of comparative buffer and spacer layer engineering and provide materials insights into the design of Co/Pt-based p-SAF reference stacks that may inform future p-MTJ structures. Full article

Multiband solar cells offer a promising route to surpass the Shockley-Queisser limit by harnessing sub-bandgap photons through three active energy band transitions. However, realizing their full potential requires overcoming key challenges in material design and device architecture. Here, we propose a novel multiband stacked anti-parallel junction solar cell structure based on highly mismatched alloys (HMAs), in particular dilute GaAsN with ~1–4% N. An anti-parallel junction consists of two semiconductor junctions connected with opposite polarity, enabling bidirectional current control. The structures of the proposed devices are based on dilute GaAsN with anti-parallel junctions, which allow the elimination of tunneling junctions—a critical yet complex component in conventional multijunction solar cells. Semiconductors with three active energy bands have demonstrated the unique properties of carrier transport through the stacked anti-parallel junctions via tunnel currents. By leveraging highly mismatched alloys with tailored electronic properties, our design enables bidirectional carrier generation through forward- and reverse-biased diodes in series, significantly enhancing photocurrent extraction. Through detailed SCAPS-1D simulations, we demonstrate that strategically placed blocking layers prevent carrier recombination at contacts while preserving the three regions of photon absorption in a single multiband semiconductor p/n junction. Remarkably, our optimized five-stacked anti-parallel junctions structure achieves a maximum theoretical conversion efficiency of 70% under 100 suns illumination, rivaling the performance of state-of-the-art six-junctions III-V solar cells—but without the fabrication complexity of multijunction solar cells associated with tunnel junctions. This work establishes that highly mismatched alloys are a viable platform for high efficiency solar cells with simplified structures. Full article

A state-of-the-art tunnel magnetoresistance (TMR) sensor architecture, which is based on the perpendicularly magnetized magnetic tunnel junction (pMTJ), is introduced and engineered for ultrafast, high thermal stability, and linearity for magnetic field detection. Limitations in high-frequency environments, stemming from insufficient thermal stability and slow recovery times in conventional TMR sensors, are overcome by this approach. The standard MRAM structure is modified, and the Ruderman–Kittel–Kasuya–Yosida (RKKY) interaction is employed to give a strong, internal restoring torque to the storage layer magnetization. Sensor linearity is also ensured by this RKKY mechanism, and rapid relaxation to the initial spin state is observed when an external field is removed. The structural and magnetic properties of the multilayer stack are experimentally demonstrated. Robust synthetic antiferromagnetic (SAF) coupling is confirmed by using polar MOKE spectroscopy with an optimal Ru insertion layer thickness (0.6 nm), which is essential for high thermal stability. Subsequently, an ultrafast response of this TMR sensor architecture is probed by micromagnetic simulations. The storage layer magnetization rapidly recovers to the SAF state within an ultrashort time of 5.78 to 5.99 ns. This sub-6 ns recovery time scale suggests potential operation into the hundreds of MHz range. Full article

As an emerging type of non-volatile memory, magneto-resistive random access memory (MRAM) stands out for its exceptional reliability and rapid read–write speeds, thereby garnering considerable attention within the industry. The memory cell architecture of MRAM is centered around the magnetic tunnel junction (MTJ), which, however, is prone to interference from external magnetic fields—a limitation that restricts its application in demanding environments. To address this challenge, we propose an innovative open magnetic shielding structure. This design demonstrates remarkable shielding efficacy against both in-plane and perpendicular magnetic fields, effectively catering to the magnetic shielding demands of both spin-transfer torque (STT) and spin–orbit torque (SOT) MRAM. Finite element magnetic simulations reveal that when subjected to an in-plane magnetic field of 40 mT, the magnetic field intensity at the chip level is reduced to nearly 1‰ of its original value. Similarly, under a perpendicular magnetic field of 40 mT, the magnetic field at the chip is reduced to 2‰ of its initial strength. Such reductions significantly enhance the anti-magnetic capabilities of MRAM. Moreover, the magnetic shielding performance remains unaffected by the height of the packaging structure, ensuring compatibility with various chip stack packaging requirements across different layers. The research presented in this paper holds immense significance for the realization of highly reliable magnetic shielding packaging solutions for MRAM. Full article

Multilayer heterostructures of [(BiFeO₃)_m/(SrTiO₃)_n]_p were synthesized on ITO-coated quartz substrates via pulsed laser deposition, with varying thickness ratios (r = n/m) and periodicities (p = 1–3). Structural, electrical, and piezoelectric properties were systematically investigated using X-ray diffraction, AFM, and PFM. The BiFeO₃ layers crystallized in a distorted rhombohedral phase (R3c), free of secondary phases. Compared to single-layer BiFeO₃ films, the multilayers exhibited markedly lower leakage current densities and enhanced piezoelectric response. Electrical conduction transitioned from space-charge-limited current at low fields (E < 100 kV/cm) to Fowler–Nordheim tunneling at high fields (E > 100 kV/cm). Optimal performance was achieved for r = 0.30, p = 1, with minimal leakage (J = 8.64 A/cm² at E = 400 kV/cm) and a peak piezoelectric coefficient (d₃₃ = 55.55 pm/V). The lowest coercive field (Ec = 238 kV/cm) occurred in the configuration r = 0.45, p = 3. Saturated hysteresis loops confirmed stable ferroelectric domains. These findings demonstrate that manipulating layer geometry in [(BiFeO₃)_m/(SrTiO₃)_n]_p stacks significantly enhances functional properties, offering a viable path toward efficient, lead-free piezoelectric nanodevices. Full article

Given the high casualty rate on expressways, this study aimed to accurately predict traffic accident rates and the key factors influencing them. Taking an expressway in Southern China as the research object, we constructed a two-layer stacking model integrating neural networks and tree models, based on accident data, traffic flow data, and road segment characteristic data. Six base models were integrated for prediction, and the Shapley Additive exPlanations (SHAP) method was used to analyze influencing factors. Results showed that the proposed model achieved the best performance, with a root mean square error (RMSE) of 11.05 and a mean absolute error (MAE) of 6.12, and its performance was significantly superior to that of other models (p < 0.05). Results from hyperparameter optimization and 5-fold cross-validation indicated that the proposed model had an RMSE of 8.91 ± 2.03, which was better than that of other models. Among all input factors, the proportion of tunnel length to total length and the variance of bridge width had the most significant impact on the expressway traffic accident rate, while the average width of tunnels had the lowest impact. This study realizes accurate prediction using widely available data and clarifies key factor mechanisms, providing support for expressway safety management and early risk warnings. Full article

We present a comprehensive vibrational spectroscopic analysis of vertical molecular junction devices constructed using single-layer graphene electrodes separated by an aryl alkane monolayer. In this work, inelastic electron tunneling spectroscopy (IETS) is employed to probe molecular vibrations within the junction, providing an in situ fingerprint of the molecules. Graphene has emerged as a promising electrode material for molecular electronics due to its atomically thin, mechanically robust nature and ability to form stable contacts. However, prior to this study, the vibrational spectra of molecules in graphene-based molecular junctions had not been fully explored. Here, we demonstrate that vertically stacked graphene electrodes can be used to form stable and reproducible molecular junctions that yield well-resolved IETS signatures. The observed IETS spectra exhibit distinct peaks corresponding to the vibrational modes of the sandwiched aryl alkane molecules, and all major features are assigned through density functional theory calculations of molecular vibrational modes. Furthermore, by analyzing the broadening of IETS peaks with temperature and AC modulation amplitude, we extract intrinsic vibrational linewidths, confirming that the spectral features originate from the molecular junction itself rather than extrinsic noise or instrumental artifacts. These findings conclusively verify the presence of the molecular layer between graphene electrodes as the charge transport pathway and highlight the potential of graphene–molecule–graphene junctions for fundamental studies in molecular electronics. Full article

Deep neural networks have been widely applied to fiber optic sensor systems, where the detection of external intrusion in metro tunnels is a major challenge; thus, how to achieve the optimal balance between resource consumption and accuracy is a critical issue. To address this issue, we propose a lightweight deep learning model, the Temporal Efficient Residual Network (TEResNet), for the detection of anomalous intrusion. In contrast to the majority of two-dimensional convolutional approaches, which require a deep architecture to encompass both low- and high-frequency domains, our methodology employs temporal convolutions and a compact residual network architecture. This allows the model to incorporate lower-level features into the higher-level feature formation in subsequent layers, leveraging informative features from the lower layers, and thus reducing the number of stacked layers for generating high-level features. As a result, the model achieves a superior performance with a relatively small number of layers. Moreover, the two-dimensional feature map is reduced in size to reduce the computational burden without adding parameters. This is crucial for enabling rapid intrusion detection. Experiments were conducted in the construction environment of the Guangzhou Metro, resulting in the creation of a dataset containing 6948 signal segments, which is publicly accessible. The results demonstrate that TEResNet outperforms the existing intrusion detection methods and advanced deep learning networks, achieving an accuracy of 97.12% and an F1 score of 96.15%. With only 48,009 learnable parameters, it provides an efficient and reliable solution for intrusion detection in metro tunnels, aligning with the growing demand for lightweight and robust information processing systems. Full article

Defects in the free layer are considered to be the main cause of the balloon effect, but there is little insight into the synthetic antiferromagnetic (SAF) layer. To address this shortcoming, in this work, an optimized SAF layer was introduced in the perpendicular magnetic tunneling junction (pMTJ) stack to eliminate the low-probability bifurcated-switching phenomenon. The results indicated that the Hf field in the film stack improved significantly from ~5700 Oe to ~7500 Oe. A magnetoresistive random access memory (MRAM) test chip was also fabricated with a 300 mm process, resulting in a significantly improved ballooning effect. The results also indicated that the switching voltage decreased by 18.6% and the writing energy decreased by 33.7%. In addition, the low-probability stray field along the x-axis was thought to be the main cause of the ballooning effect, and was experimentally optimized for the first time by enhancing the SAF layer. This work provides a new perspective on spin-flipping dynamics, facilitating a deeper comprehension of the internal mechanism and helping to secure improvements in MRAM performance. Full article

The current deformation and stable state of slopes with historical shatter signs is a concern for engineering construction. Suspected landslide scarps were discovered at the rear edge of the Genie slope on the Tibetan Plateau during a field investigation. To qualitatively determine the current status of the surface deformation of this slope, this study used high-resolution optical remote sensing, airborne light detection and ranging (LiDAR), and interferometric synthetic aperture radar (InSAR) technologies for comprehensive analysis. The interpretation of high-resolution optical and airborne LiDAR data revealed that the rear edge of the slope exhibits three levels of scarps. However, no deformation was detected with differential InSAR (D-InSAR) analysis of ALOS-1 radar images from 2007 to 2008 or with Stacking-InSAR and small baseline subset InSAR (SBAS-InSAR) processing of Sentinel-1A radar images from 2017 to 2020. This study verified the credibility of the InSAR results using the standard deviation of the phase residuals, as well as in-borehole displacement monitoring data. A conceptual model of the slope was developed by combining field investigation, borehole coring, and horizontal exploratory tunnel data, and the results indicated that the slope is composed of steep anti-dip layered dolomite limestone and that the scarps at the trailing edges of the slope were caused by historical shallow toppling. Unlike previous remote sensing studies of deformed landslides, this paper argues that remote sensing results with reliable accuracy are also applicable to the study of undeformed slopes and can help make preliminary judgments about the stability of unexplored slopes. The study demonstrates that the long-term consistency of InSAR results in integrated remote sensing can serve as an indicator for assessing slope stability. Full article

In this work, the implementation of HfZrO layers for the tunneling, charge trapping, and blocking mechanisms within the device offer benefits in terms of programmability and data retention. This configuration has resulted in a memory device that can achieve a significant difference in threshold voltage of around 2 V per memory level. This difference is crucial for effectively distinguishing between multiple levels of memory in MLC applications. Additionally, the device operates at low programming voltages below 14 V. Furthermore, the device showcases impressive endurance and data retention capabilities, maintaining a large memory window over extended periods and under varying temperature conditions. The advancement in the a-IGZO-based memory device, characterized by its uniform oxide stacking, presents a viable solution to the industry’s requirement for memory storage options that are efficient, dependable, and economical. Full article

The cis- and trans-isomers of 6-(3-(3,4-dichlorophenyl)-1,2,4-oxadiazol-5-yl)cyclohex-3-ene-1-carboxylic acid (cis-A and trans-A) were obtained by the reaction of 3,4-dichloro-N′-hydroxybenzimidamide and cis-1,2,3,6-tetrahydrophthalic anhydride. Cocrystals of cis-A with appropriate solvents (cis-A‧½(1,2-DCE), cis-A‧½(1,2-DBE), and cis-A‧½C₆H₁₄) were grown from 1,2-dichloroethane (1,2-DCE), 1,2-dibromoethane (1,2-DBE), and a n-hexane/CHCl₃ mixture and then characterized by X-ray crystallography. In their structures, cis-A is self-assembled to give a hybrid 2D supramolecular organic framework (SOF) formed by the cooperative action of O–H⋯O hydrogen bonding, Cl⋯O halogen bonding, and π⋯π stacking. The self-assembled cis-A divides the space between the 2D SOF layers into infinite hollow tunnels incorporating solvent molecules. The energy contribution of each noncovalent interaction to the occurrence of the 2D SOF was verified by several theoretical approaches, including MEP and combined QTAIM and NCIplot analyses. The consideration of the theoretical data proved that hydrogen bonding (approx. −15.2 kcal/mol) is the most important interaction, followed by π⋯π stacking (approx. −11.1 kcal/mol); meanwhile, the contribution of halogen bonding (approx. −3.6 kcal/mol) is the smallest among these interactions. The structure of the isomeric compound trans-A does not exhibit a 2D SOF architecture. It is assembled by the combined action of hydrogen bonding and π⋯π stacking, without the involvement of halogen bonds. A comparison of the cis-A structures with that of trans-A indicated that halogen bonding, although it has the lowest energy in cis-A-based cocrystals, plays a significant role in the crystal design of the hybrid 2D SOF. The majority of the reported porous halogen-bonded organic frameworks were assembled via iodine and bromine-based contacts, while chlorine-based systems—which, in our case, are structure-directing—were unknown before this study. Full article

The requirements for ever-increasing volumes of data storage have urged intensive studies to find feasible means to satisfy them. In the long run, new device concepts and technologies that overcome the limitations of traditional CMOS-based memory cells will be needed and adopted. In the meantime, there are still innovations within the current CMOS technology, which could be implemented to improve the data storage ability of memory cells—e.g., replacement of the current dominant floating gate non-volatile memory (NVM) by a charge trapping memory. The latter offers better operation characteristics, e.g., improved retention and endurance, lower power consumption, higher program/erase (P/E) speed and allows vertical stacking. This work provides an overview of our systematic studies of charge-trapping memory cells with a HfO₂/Al₂O₃-based charge-trapping layer prepared by atomic layer deposition (ALD). The possibility to tailor density, energy, and spatial distributions of charge storage traps by the introduction of Al in HfO₂ is demonstrated. The impact of the charge trapping layer composition, annealing process, material and thickness of tunneling oxide on the memory windows, and retention and endurance characteristics of the structures are considered. Challenges to optimizing the composition and technology of charge-trapping memory cells toward meeting the requirements for high density of trapped charge and reliable storage with a negligible loss of charges in the CTF memory cell are discussed. We also outline the perspectives and opportunities for further research and innovations enabled by charge-trapping HfO₂/Al₂O₃-based stacks. Full article